Exploring the factors influencing e-bike road safety: A survey study based on the experiences of Taiwanese cyclists

Huang, Fei-Hui

doi:10.1016/j.ergon.2022.103292

Cited by 6 publications

(4 citation statements)

References 23 publications

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“…The studies included in this review have measured cardiovascular parameters using different types of sensors. Electrode-based ECG has been the most frequently used data collection hardware for HR and HRV data [ 21 , 30 , 52 , 54 , 56 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 ]. HR and HRV analysis typically requires three leads in the ECG to detect the R peak in the QRS complex [ 74 ].…”

Section: Resultsmentioning

confidence: 99%

“…The basic principle of DALI mimics the NASA-TLX, with six pre-defined factors, and only varies in the choice of the factors involved in defining the workload score. The scale has been used in several automotive studies and has proven to be advantageous for identifying the origin of the driver’s MWL [ 21 , 22 , 23 ]. Although subjective measures are simple and easy to implement, the assumption is that humans are capable of recognising increases in workload demands.…”

Section: Introductionmentioning

confidence: 99%

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A Systematic Review of In-Vehicle Physiological Indices and Sensor Technology for Driver Mental Workload Monitoring

Sriranga

Birrell

2023

Sensors

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The concept of vehicle automation ceases to seem futuristic with the current advancement of the automotive industry. With the introduction of conditional automated vehicles, drivers are no longer expected to focus only on driving activities but are still required to stay alert to resume control. However, fluctuations in driving demands are known to alter the driver’s mental workload (MWL), which might affect the driver’s vehicle take-over capabilities. Driver mental workload can be specified as the driver’s capacity for information processing for task performance. This paper summarizes the literature that relates to analysing driver mental workload through various in-vehicle physiological sensors focusing on cardiovascular and respiratory measures. The review highlights the type of study, hardware, method of analysis, test variable, and results of studies that have used physiological indices for MWL analysis in the automotive context.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Systematic Review of In-Vehicle Physiological Indices and Sensor Technology for Driver Mental Workload Monitoring

Sriranga

Birrell

2023

Sensors

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“…Obviously, the higher the manufacturing cost of the motor with better performance, the more likely to affect the price of the electric bicycle [35,36]. Second, regarding the effect of power of engine (C 5 ) on safety (C 8 ), nowadays, in order to ensure safety, the maximum output power of engine is only 400 watts and the maximum riding speed is limited to 25 km/h, and the motor has a 3-second automatic power supply stop setting to provide safety to Complexity users when the speed exceeds the speed limit, braking situation, short circuit, or malfunction of signal system [36,48]. In terms of the effect of power of engine (C 5 ) on battery durability (C 3 ), the motor requires electricity to operate, and the speed can be effectively controlled by regulating the voltage level.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Mutual Influence Relationships of Purchase Intention Factors of Electric Bicycles: Application of DEMATEL Taking into Account Information Uncertainty and Expert Confidence

et al. 2022

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As the negative environmental impacts of transportation systems become more severe, governments and environmental groups are seeking more sustainable transportation options, such as replacing fuel-powered vehicles with electric vehicles and expanding public transportation systems to reduce the number of people driving on their own, in order to reduce the environmental impacts of transportation systems. At present, the rapid expansion of public transportation systems is not an easy task and requires a long period of time to plan for expansion and construction, so people are increasingly looking to find means of transportation that meet sustainable conditions as solutions. In this context, electric bicycles are one of the solutions that people can choose, with benefits such as energy saving, carbon reduction, effective air pollution reduction, and simple and labor-saving riding. However, in Taiwan, despite the many benefits of electric bicycles, their popularity is not high. Therefore, this study focuses on the factors that affect the purchase of electric bicycles in Taiwan. The Influential Network Relation Map (INRM) generated by the Z-based Decision-making Trial and Evaluation Laboratory (Z-DEMATEL) technique is used to describe the influence relationships among the factors and to establish the key evaluation criteria of electric bicycle purchase intention. The results indicate that vehicle price, safety, motor performance, battery life, and battery durability are the most important factors in purchasing electric bicycles. Furthermore, the power of motor is considered as the factor that most significantly affects other criteria, while safety and price are most likely to be affected by other criteria. This study has contributed to academia and industry, for the dependency weights of these factors are set to provide a scientific and systematic way to show how consumers think in the decision-making process and to provide more reliable information and management implications for the electric bicycle industry.

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“…When the crash occurred in the pedestrian walkway, the two parties to the confict were mainly motorized two-wheelers and bicycles, which are all roadvulnerable groups. After the competition, the possibility of injury to the rider is reduced; in the presence of illegal behavior scenarios occurring in the nonmotorized roadway, the possibility of minor injuries to the rider is reduced, compared to the motor vehicle roadway, electric twowheeled vehicles in the nonmotorized lane driving in the event of a crash when the object of the confict is mainly for the vulnerable groups of the roadway such as electric twowheeled vehicles, bicycles, generally slower speeds, the possibility of injuries in the event of a crash is lower, in some study also found that riders who crashed on multi-use paths, sidewalks, and local streets tended to sufer more severe injuries [22,23].…”

Section: Road Factor Analysismentioning

confidence: 99%

Analysis of Factors Affecting the Severity of Injuries in Electric Two‐Wheeled Vehicle Crashes with or without Violation: A Random Parametric Logit Model considering Heterogeneity of Means and Variances

Wei,

Han,

Guo

et al. 2024

Journal of Advanced Transportation

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Electric two-wheeled vehicle is one of the main commuting tools in China, but they are also more likely to have violations of the road group. In order to study the effect of the presence of violation on the severity of road traffic crashes among electric two-wheeler riders, in this study, the effects of rider characteristics, road characteristics, collision characteristics, and environmental characteristics on the severity of injuries of electric two-wheeled vehicle riders were considered separately analyzed based on the data of 6403 two-wheeled electric vehicle traffic crashes in a region of Shandong Province from 2015 to 2021, and a random parametric logit model considering the heterogeneity of the mean and the variance (RP-HMV logit) was established based on the presence or absence of violation behaviors of riders, respectively, in order to explore unobserved heterogeneity. In order to test the validity of the model for modeling the injury severity of pedestrians riding electric two-wheelers, multinomial logit (MN-logit model), and random parameter logit model (RP-logit) were estimated, and the results showed that the RP-HMV logit model was significantly superior in terms of goodness of fit. The study showed that some of the factors differed somewhat between the two scenarios, such as gender, while the factors that were significant in both scenarios were >60, broken pavement, street lights at night, no street lights at night, mixed motorized and nonmotorized lanes, sidewalks, other angles, no control, severe weather, and visibility <200 m, where the severe weather and visibility <200 m were random parameters obeying normal distributions, there is a significant difference between having street lights and no control at night in both scenarios, and the difference is significant. The results of the study can provide a reference for the development of targeted countermeasures to improve the traffic safety of electric two-wheeled vehicles in China.

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Exploring the factors influencing e-bike road safety: A survey study based on the experiences of Taiwanese cyclists

Cited by 6 publications

References 23 publications

A Systematic Review of In-Vehicle Physiological Indices and Sensor Technology for Driver Mental Workload Monitoring

A Systematic Review of In-Vehicle Physiological Indices and Sensor Technology for Driver Mental Workload Monitoring

Analysis of Mutual Influence Relationships of Purchase Intention Factors of Electric Bicycles: Application of DEMATEL Taking into Account Information Uncertainty and Expert Confidence

Analysis of Factors Affecting the Severity of Injuries in Electric Two‐Wheeled Vehicle Crashes with or without Violation: A Random Parametric Logit Model considering Heterogeneity of Means and Variances

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